Total return to shareholder analytics

ABSTRACT

A computer-implemented method for analyzing the relative performance of a business unit of a company is provided. The method may include: receiving financial data about the business unit; determining with a data processor NOPLAT, revenue, capital charge, and invested capital values for the business unit at least at a first time and a second time from the financial data; determining with the data processor at least two data point from the NOPLAT, revenue, capital charge, and invested capital values, each data point including a first component indicative of NOPLAT/revenue for the business unit and a second component indicative of revenue/capital charge for the business unit, the at least two data points indicative of values determined at one of the first time and the second time, respectively; and displaying, to advise a user of the performance of the business unit, the at least two data points, a first indicia for each data point indicative of the capital value, a second indicia indicative of a spread percentage, and a third indicia indicative of a relationship between the at least two data points between the first time and the second time.

RELATED APPLICATIONS

The present patent document claims the benefit of the filing date under 35 U.S.C. §119(e) of Provisional U.S. Patent Application Ser. No.60/549,619, filed Mar. 2, 2004, which is hereby incorporated by reference.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever. The following notice applies to any software and data as described below and in the drawings hereto: Copyright© 2005, Accenture, All Rights Reserved.

BACKGROUND

1. Technical Field

The present invention relates generally to business performance management, and more particularly to a system and method for evaluating a company's performance based on the decomposition and mapping of total return to shareholders.

2. Background Information

Business performance management (BPM), also known as Enterprise performance management (EPM), relates to the execution and monitoring of the performance of various components of a company's business. BPM, sometimes referred to as the next generation of business intelligence (BI), focuses on business processes such as planning and forecasting and helps businesses discover efficient use of their business units, financial, human, and material resources. Typically, BPM systems consolidate data from various sources, and provide functions for querying and analyzing the data and putting the results into practice.

BPM enhances business processes by creating better feedback loops that allow for the continuous, real-time review of information to help identify and eliminate problems before they grow. For example, forecasting capabilities may help the company take corrective action in time to meet earnings projections. BPM may also be useful in risk analysis and predicting outcomes of merger and acquisition scenarios, as well as planning to overcome potential problems.

BPM provides key performance indicators (KPI), or performance metrics, that help companies monitor efficiency of projects and employees against operational targets. These metrics/KPI may be used to assess the present state of the business and to prescribe a course of action. For example, BPM systems have been used to analyze: New customers acquired; Status of existing customers; Attrition of customers; Turnover generated by segments of the Customers; Outstanding balances held by segments of customers and terms of payment; Collection of bad debts within customer relationships; Demographic analysis of individuals (potential customers) applying to become customers, and the levels of approval, rejections and pending numbers; Delinquency analysis of customers behind on payments; and Profitability of customers by demographic segments and segmentation of customers by profitability. Regardless of the type of analysis a BPM system may be used for, BPM systems must acquire metric/KPI that is consistent, correct, and timely available.

Despite the great benefits many BPM systems provide, these systems are only as powerful as the metrics/KPI used to benchmark business performance. Unfortunately, there is a disconnect in traditional BPM systems between the financial performance metrics companies use in analyzing business performance and the ability to create and sustain high performance results in their execution over time. This disconnect arises because most companies take an internal approach to evaluating their business performance using performance metrics such as Earnings per Share (EPS), Return on Net Assets (RONA), Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA), Return on Investment Capital (ROIC), Economic Value Added (EVA), Cash Flow Return on Investment (CFROI), and the like. These metrics neglect the true drivers of sustainable shareholder value and instead only determine the operating performance for the current operating year. Essentially, these metrics only provide analysis of a company's current value, or the present value of the uniform perpetual earnings on assets currently held by the company.

This disconnect becomes even more apparent when analyzing companies such as biotech companies with a high percentage of future value, or the present value of company opportunities for investments in real assets that will yield more than the normal market rate of return. For example, traditional value management focuses on Net Operating Profit Less Adjusted Taxes (NOPLAT) as the only source of “Return” on Invested Capital. Because high future value firms have little or no NOPLAT, there is no accounting for the value created by these types of companies.

Companies attempt to solve this disconnect through the implementation of major new transactional systems or point solutions to specific problems, such as ERP systems and data warehouses. Although these solutions are good at tracking transactional data, they do not help a company plan for what may occur and track the key drivers to enable decision making. Point solutions are band-aides that don't address the real problem of proactively managing those aspects of business performance that contribute to sustainable shareholder value.

Other companies address the current problems with BPM by implementing a Balanced Scorecard or Executive Dashboard. Exemplary scorecards and dashboards include the Cognos® Metrics Manager and Cognos® Visualizer, provided by Cognos, Inc. of Ottawa, Canada, and the Hyperion Performance Scorecard, provided by Hyperion Solutions Corporation of Sunnyvale, California. These solutions attempt to capture the financial and non-financial drivers of value for the company. These solutions typically provide results that are useful and insightful. However, these solutions may not be integrated into the remaining BPM systems utilized by the company, and may not incorporate metrics reflective of the true drivers of shareholder values.

Accordingly, there is a need for software tools and information technology solutions to create an integrated capability to drive BPM strategy and value creation that accurately measures the key drivers of both current and future value from an external perspective as well as detail how these drivers interrelate.

BRIEF SUMMARY

In one aspect, a computer-implemented method for analyzing the relative performance of a business unit of a company is provided. The method may include: receiving financial data about the business unit; determining with a data processor NOPLAT, revenue, capital charge, and invested capital values for the business unit at least at a first time and a second time from the financial data; determining with the data processor at least two data points from the NOPLAT, revenue, capital charge, and invested capital values, each data point including a first component indicative of NOPLAT/revenue for the business unit and a second component indicative of revenue/capital charge for the business unit, the at least two data points indicative of values determined at one of the first time and the second time, respectively; and displaying, to advise a user of the performance of the business unit, the at least two data points, a first indicia for each data point indicative of the capital value, a second indicia indicative of a spread percentage, and a third indicia indicative of a relationship between the at least two data points between the first time and the second time.

In another embodiment, computer-implemented method for analyzing the relative performance of a business unit of a company, the method comprising: receiving financial data about the business unit; determining with a data processor spread percentage, future value, and invested capital values for the business unit at least at a first time and a second time from the financial data; determining with a data processor at least two data point from the spread percentage, future value, and invested capital values, each data point including a first component indicative of spread percentage for the business unit and a second component indicative of future value/invested capital for the business unit, the at least two data points indicative of values determined at one of the first time and the second time, respectively; and displaying, to advise a user of the performance of the business unit, the at least two data points, a first indicia for each data point indicative of the invested capital value and a second indicia indicative of a relationship between the at least two data points between the first time and the second time.

These and other embodiments and aspects of the invention are described with reference to the noted Figures and the below detailed description of the preferred embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a diagram representative of an exemplary system for implementing one embodiment;

FIG. 1B is a diagram representative of an exemplary architecture for a BPM system;

FIG. 2 is a diagram representative of an exemplary EPM technical architecture for implementing one embodiment;

FIG. 3 is a diagram representative of an exemplary framework for delivering an integrated BPM system;

FIG. 4A is a diagram representative of one embodiment of a Total Return to Shareholder (TRS) map depicting exemplary interrelations between internal and external business metrics;

FIG. 4B is a diagram representative of a second embodiment of a TRS map depicting exemplary interrelations between internal and external business metrics;

FIG. 4C is a diagram representative of a third embodiment of a TRS map depicting exemplary interrelations between internal and external business metrics;

FIG. 5A is a diagram representative of a computer display of a first part of an exemplary calculation worksheet;

FIG. 5B is a diagram representative of a computer display of second part of an exemplary calculation of Total Economic Profit (TEP);

FIG. 6 is a diagram representative of an TRS calculation using the TEP performance metric;

FIG. 7 is an exemplary comprehensive performance analysis tool;

FIG. 8 is an exemplary forecast input interface for the analysis tool of FIG. 7;

FIG. 9 is an exemplary intermediate report for the analysis tool of FIG. 7;

FIG. 10 is another exemplary intermediate report for the analysis tool of FIG. 7;

FIG. 11 is another exemplary intermediate report for the analysis tool of FIG. 7;

FIG. 12 is another exemplary intermediate report for the analysis tool of FIG. 7;

FIG. 13 is another exemplary intermediate report for the analysis tool of FIG. 7;

FIG. 14 is an exemplary summary report for the analysis tool of FIG. 7;

FIG. 15 is an exemplary visualization for the analysis tool of FIG. 7;

FIG. 16 is another exemplary visualization for the analysis tool of FIG. 7; and

FIG. 17 is an exemplary navigation tool for the analysis tool of FIG. 7.

DETAILED DESCRIPTION OF THE DRAWINGS AND THE PRESENTLY PREFERRED EMBODIMENTS

Referring now to the drawings, and initially to FIG. 1, an exemplary system for implementing the invention includes a general purpose computing device in the form of a computing environment 20, including a processing unit 32, a system memory 22, and a system bus 38, that couples various system components including the system memory 22 to the processing unit 32. The processing unit 32 may perform arithmetic, logic and/or control operations by accessing system memory 22. The system memory 22 may store information and/or instructions for use in combination with processing unit 32. The system memory 22 may include volatile and non-volatile memory, such as random access memory (RAM) 24 and read only memory (ROM) 30. A basic input/output system (BIOS) containing the basic routines that helps to transfer information between elements within the computer environment 20, such as during start-up, may be stored in ROM 30. The system bus 38 may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures.

The computing environment 20 may further include a hard disk drive 42 for reading from and writing to a hard disk (not shown), and an external disk drive 46 for reading from or writing to a removable external disk 48. The removable disk may be a magnetic disk for a magnetic disk driver or an optical disk such as a CD ROM for an optical disk drive. The hard disk drive 42 and external disk drive 46 are connected to the system bus 38 by a hard disk drive interface 40 and an external disk drive interface 44, respectively. The drives and their associated computer-readable media provide nonvolatile storage of computer readable instructions, data structures, program modules and other data for the computing environment 20. Although the exemplary environment described herein employs a hard disk and an external disk 48, it should be appreciated by those skilled in the art that other types of computer readable media which can store data that is accessible by a computer, such as magnetic cassettes, flash memory cards, random access memories, read only memories, and the like, may also be used in the exemplary operating environment.

A number of program modules may be stored on the hard disk, external disk 48, ROM 30 or RAM 24, including an operating system (not shown), one or more application programs 26, other program modules (not shown), and program data 28. One such application program may include the functionality as detailed below.

A user may enter commands and/or information, as discussed below, into the computing environment 20 through input devices such as mouse 56 and keyboard 58. Other input devices (not shown) may include a microphone (or other sensors), joystick, game pad, scanner, or the like. These and other input devices may be connected to the processing unit 32 through a serial port interface 54 that is coupled to the system bus 38, or may be collected by other interfaces, such as a parallel port interface 50, game port or a universal serial bus (USB). Further, information may be printed using printer 52. The printer 52, and other parallel input/output devices, may be connected to the processing unit 32 through parallel port interface 50. A monitor 36, or other type of display device, is also connected to the system bus 38 via an interface, such as a video input/output 34. In addition to the monitor 36, computing environment 20 may include other peripheral output devices (not shown), such as speakers or other audible output.

The computing environment 20 may communicate with other electronic devices such as remote computer 68. Remote computer 68 may be another computing environment such as a server, router, network PC, peer device, telephone (wired or wireless), personal digital assistant, television, or the like. Remote computer 68 may include many or all of the elements described above relative to the computing environment 20. In one embodiment, the remote computer 68 is a server coupled with a database of historical financial data for a plurality of companies. Herein, the phrase “coupled with” is defined to mean directly connected to or indirectly connected with through one or more intermediate components. Such intermediate components may include both hardware and software based components. Alternatively, or in addition, the remote computer may include accounting and/or financial software for maintaining a company's internal recording keeping.

To communicate, the computer environment 20 may operate in a networked environment using connections (wired, wireless or both wired and wireless) to one or more electronic devices. FIG. 1 depicts the computer environment networked with remote computer 68 and with information hub 150 of a distributed computer system for business performance management, as shown in FIG. 1B. The logical connections depicted in FIG. 1 include a local area network (LAN) 64 and a wide area network (WAN) 66. Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets and the Internet.

When used in a LAN networking environment, the computing environment 20 may be connected to the LAN 64 through a network I/O 62. When used in a WAN networking environment, the computing environment 20 may include a modem 60 or other means for establishing communications over the WAN 66. The modem 60, which may be internal or external to computing environment 20, is connected to the system bus 38 via the serial port interface 54. In a networked environment, program modules depicted relative to the computing environment 20, or portions thereof, may be stored in a remote memory storage device resident on or accessible to remote computer 68. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the electronic devices may be used.

The new business performance management system and method is typically provided as software running on the processing unit 32, resident in the computer-readable medium of the storage device 42, to allow the processing unit 32 to provide the functionalities described herein. As described below, the software may be provided as a spreadsheet, for example as implemented on a spreadsheet program such as Microsoft Excel, however one skilled in the art would realize that the software may be provided as a stand-alone software program (i.e., implemented in any suitable programming language) operating on the processing unit 32 or any operating system provided therewith, and need not utilize any additional software operating on the system. Alternatively, or in addition, the functionalities may be provided as a combination of software and one or more ASICs to provide the functionalities discussed herein.

In further embodiments, as described below, the functionalities may also be provided as a web-based application running on a browser and accessible via the Internet or other communications network. Alternatively, the functionalities disclosed herein may be incorporated into an Executive Dashboard, described above. In yet another embodiment, the functionalities disclosed herein may be provided as a benchmarking service that analyzes historical data for a plurality of companies. The historical data may reside in a remote database, or may be internal to the benchmarking service. The benchmarking service may provide industry specific data and comparative benchmarks for particular industries, or provide general benchmarks that span multiple industries. In one embodiment, the functionalities are embedded into the architecture of a BPM management system via an information hub 150.

An exemplary BPM architecture 100 is shown in FIG. 1B. The architecture 100 may include various source systems 102, reference data 110, applications 120, and reporting and analysis tools 130 integrated by an information hub 150 that may provide support for collaboration of business units, workflow process management, security, and system administration. The source systems 102 may capture information about the company from various data sources 104 via various methods 106. Exemplary data sources 104 may include Enterprise Resource Planning systems (ERP), which are integrated information system that uses packaged software to serve any or all departments within an enterprise. For example, ERP systems may provide software for manufacturing, order entry, accounts receivable and payable, general ledger, purchasing, warehousing, transportation and human resources departments. Additional exemplary data sources 104 may include legacy systems as well as non-financial and external sources of data, and the like. Exemplary methods 106 for managing data from the data sources 104 may include Extraction, Transformation and Loading (ETL), which may be used copy data between databases of different types, Enterprise Application Integration (EAI), which may be used to integrate applications within the company, Enterprise Intelligence Integration (EII, also known as Enterprise Information Integration), which may aggregate disparate sources 104 of business information into a single analyzable body of information, and the like.

The architecture 100 may also include reference data 110 that may define various definitions, standards, and the like. For example, the company may reference certain KPI definitions 112, reporting hierarchies 114, data standards 116, and code of authorities 118. Applications 120 may also be included to provide strategic analysis in areas such as planning/modeling 122, budgeting/forecasting 124, consolidations 126, and dimensional profitability/ABC 128. Finally, reporting and analysis tools 130 may also be provided to present the analytical results to business managers via useful reports, visualizations, and the like. Traditional BPM systems may provide, for example, reporting tools for external reporting 132, internal reporting 134, and standard reporting 136. Additionally, or alternatively, tools may be provided for ad hoc database querying 138, such as OnLine Analytical Processing (OLAP) software that allows the user to quickly analyze information that has been summarized into multidimensional views and hierarchies, executive scoreboards or dashboards 140, data mining tools 142, and the like. It should be apparent to one of ordinary skill in the art, that the source systems 100, reference data 110, applications 120, reporting and analysis tools 140, and information hub 150 capabilities necessary for a particular company may be implementation dependent, and that exact combination of tools provided may vary greatly without departing from the spirit and scope of the present invention.

Referring to FIG. 2, an exemplary framework 200 for delivering an integrated BPM system is shown. The framework 200 defines a process to drive strategy through to execution, with results informing periodic adjustments to both long and short term business tactics. The framework includes strategic planning 210, creating a business plan and target setting 220, managing operations 230, monitoring results 240, and enablers 250. The framework 200 also allows each of these areas to adapt 260 as results indicate. Exemplary strategic planning 210 tasks include environmental assessment, competitor assessment, analysis of business opportunities and key capabilities, and long-range financial planning. Exemplary tasks associated with business planning and targeted setting 220 include establishing a direction for products and services, determining the required capabilities, key initiatives, and determining revenue, cost and capital projections as well as budget and operational targets. Exemplary operational 230 tasks include setting operational targets, and managing initiatives, revenues, costs and capital. Exemplary monitoring 240 tasks include analyzing the prior period, forecasting, operational analysis, and dimensional analysis. Exemplary enablers 250 include employee incentives and rewards, and company policies and procedures.

Referring to FIG. 3, an exemplary methodology for implementing the BPM framework of FIG. 2 is shown. As described above, current methodologies focus exclusively on internal performance metrics and current year performance. When utilizing the functionality described below, however, the framework 300 provides a holistic approach to BPM that allows a company to manage business performance across various aspects of its operations and at different levels. For example, a company may want to manage the performance of their business as it effects the company's current value 370, future value 372, financing 374 or TRS value 376, described in more detail below. Alternatively or additionally, the company may wish to see its performance across any of these areas in absolute or relative terms 378, such as raw number analysis, market indices or peer group assessments, respectively. The framework 300 represents the continuous process of strategic planning 310, target setting and business plan development 320, operating 330, and monitoring performance 340 as supported by various enablers 350. An exemplary methodology for strategic planning 310 includes refining corporate vision and strategic objectives 312, determining key value drivers 314, and determining key measures of success 316 activities. The functionalities disclosed herein may find particular use in the strategic planning 310 phase when refining the corporate vision and strategic objectives 312, for example, when analyzing investor expectations, key competitor information and current and future business performance. Similarly, the functionalities disclosed herein may be used to determine the key value drivers 314, for example, by providing a mapping of the value drivers to various performance metrics, and for determining the key measures of success 316, for example, by aligning those measures with shareholder value creation to create cause and effect maps.

An exemplary methodology for target setting and business plan development 320 includes portfolio value assessment 322, set targets for key measures of accountability 324, and cascade targets to lower level metrics/organization 326 activities. As described in more detail below, the functionalities disclosed herein may find particular use in setting targets for key measures of accountability 324, for example, by aligning top down targets with shareholder expectations and ensuring the consistency of external and internal targets. Similarly, the functionalities disclosed herein are ideally suited to cascade the targets to lower level metrics 326.

Exemplary methodology activities for operations 330 include developing plans to achieve the specified targets 332, allocating resources (in terms of both capital and man-power) to achieve all business plans 334, and reviewing, challenging, and finalizing plans and forecasts 336. The functionalities disclosed herein facilitate each of these activities 332, 334, and 336 by providing a clear mapping of target values to business and operational drivers to enable bottom-up resource allocation in line with the established target values.

An exemplary methodology for monitoring performance 340 includes activities for closing and consolidating books and reporting actuals 342, monitoring key measures of business performance 344, reviewing performance with executive management 346, and developing action plans, re-allocating resources and updating forecasts. The functionalities disclosed herein facilitate performance monitoring 340 by providing a consistent system for measuring the performance of the company and a simple user interface to determine exceptions and root causes of poor performance. Coupling these functionalities with a balanced scorecard or executive dashboard, as mentioned above, further enhance these advantages.

Finally, exemplary methodology activities for enablers 350 include establishing, analyzing, and adapting employee incentive and rewards programs 352 and policies and procedures 354, and providing an integrated IT architecture 356, such as the architecture describe above in reference to FIG. 1B, or other software solution projects that utilizes an effective set of common data structures 358 and controls 360.

In order to overcome the disadvantages of the prior art BPM systems, the financial performance metrics used to analyze a company's business performance should take an external view of the company's current and future value. One such external performance metric is the Total Return to Shareholders (TRS), and is defined as the company's equity plus any dividends paid on the stock. TRS can be calculated for a given shareholder by adding dividends to any stock price appreciation and dividing the resultant value by the shareholder's original investment. Coupling the external metric TRS with internal metrics of performance allows the company to see exactly what drives shareholder value.

FIG. 4A shows an exemplary flowchart detailing the coupling of TRS with internal performance metrics and the interrelationships therein, also known as a TRS map 400. As described above, TRS 402 includes dividends 404 paid on the stock as well as the company's market value of equity or MVE 406. MVE 406 can be calculated by shares outstanding times share price. A company's debt 408 to equity structure influences its Weighted Average Cost of Capital 410 (WACC). The total market value of the company (MV) may be defined as the MVE 406 plus the market value of the debt 408.

Enterprise Value (EV) 412 (EV=MV less excess cash,411) can be decomposed into Current Value 414 (CV) and Future Value 416 (FV). The CV 414 represents the current value of the company. The CV 414 is influenced by the company's Net Operating Profits Less Adjusted Taxes 418 (NOPLAT), capital 420, and WACC 410, and can be calculated by dividing the NOPLAT 418 by the WACC 410 (which is also equal to Capital 420+EP/WACC 410), such that CV 414=NOPLAT 418/WACC 410=Capital 420+EP/WACC 410. The FV 416 represents the future value of the company, or the difference between the EV 412 and the CV 414. The FV 416 is influenced by capital 420 and the WACC 410, and can be calculated by subtracting the CV 414 from the EV 412, such that FV=EV−CV. As further detail in FIG. 4A, the capital 420 includes both balance sheet 424 and off-balance sheet 426 components. Additionally, income 422 may influence capital 420 as well as the NOPLAT 418.

The data underpinning these performance metrics also have an effect on the cash flow 434 of the company. Cash flow 434 is determined by the investments 428 made in the company, any financing arrangements 430, as well as operations 432 results. The operations 432 results are influenced by the NOPLAT 418 and the capital 420. Financing arrangements 430 influence the equity 406 of the company, its debt 408, and the ability of the company to pay dividends 404. This may affect the decision of investors to make an investment 428 in the company, which may affect the NOPLAT 418, capital 420 and Mergers and Acquistions 436 (M & A) of the company.

FIG. 4B depicts an alternative embodiment of the TRS map 400. In the embodiment of FIG. 4B, the FV 416 may be further broken down into component parts via a variety of methods, each of which attempt to define the true drivers of FV 416. For example, one may use an FV premium 440 methodology to determine a company's FV 416 growth relative to the growth of the economy (segment or index) generally. In one embodiment, the FV premium methodology 440 may decompose the FV 416 value into three components: a first component that represents an operating advantage/disadvantage for the company; a second component that defines a projected rate of growth for the economy in general; and a third component that defines the remainder of FV 416 in the company.

In the FV premium methodology 440, the first component may represent an operating advantage/disadvantage for the company. This component may define whether the company is creating or destroying value in the current period, and may be calculated, for example, by calculating a company's economic profit (EP) capitalized (EP/WACC). As described in more detail below, EP may be calculated as a company's NOPLAT less a capital charge for the company, where the capital charge may be defined as a company's invested capital times a WACC for the company, such that EP=NOPLAT−(Invested Capital*WACC). If this value is negative, the company is operating at a disadvantage and is destroying the value of capital entrusted to the company. If this value is positive, the company is operating at an advantage and has generated a premium over the value of capital that is embedded in the company's CV 414. This first component thus defines the portion of FV 416 explained by investor's expected improvement to breakeven EP.

The second component of the FV premium methodology 440 may define an implied growth of the economy in general. It should be apparent to one of ordinary skill in the art that this component may also define an implied growth rate for a particular market, market segment, industry, peer group, and the like. Additionally, this component may be determined using a variety of methods, each of which may be dependent on the market, market segment, etc. being analyzed. In one embodiment, the second component may represent an implied growth in the economy as determined by a terminal value calculation based on the US Gross Domestic Product (GDP). Typically, the terminal value of a perpetually growing firm may be defined as the Free Cash Flow of a company for the next period divided by WACC minus a terminal growth rate, or FCF_(t+1)/(WACC−g). By substituting a breakeven NOPLAT value, or the point at which zero EP is being generated, for the Free Cash Flow of the company (FTF_(t+1)) and the historical growth rate of the US GDP for the terminal growth rate (g), one can determine that portion of a company's FV 416 implied by the growth rate of the economy. In one embodiment, the breakeven NOPLAT may be defined as a company's invested capital times WACC, such that the portion of a company's FV 416 attributable to the implied growth of the economy may be calculated by the following equation: (Invested Capital*WACC)/(WACC−g). An exemplary growth rate for the US GDP is 3.41%, adjusted for inflation.

The third component, or the FV premium component, of the FV premium methodology 440 includes the remainder of any FV 416 not explained by the first two components, or the FV 416 of the company minus that portion of FV 416 explained by the implied growth of economy minus any FV 416 explained by an operating disadvantage. For companies operating at an advantage, the FV premium component may be defined as the FV 416 of the company minus that portion of FV 416 explained by the implied growth of economy. A positive FV premium component indicates that the company is outperforming the economy, market sector, industry, or the like, while a negative FV premium component indicates a growth rate below what is to be expected.

Alternatively, or additionally, other methodologies may be used to further analyze the FV 416 of a company. Exemplary methodologies include a SEER© methodology 442 that defines the drivers of FV 416, an asset methodology 444 that breaks down FV 416 by each company asset that drives FV 416, and an FV multiples methodology that analyzes a companies investments in the drivers of FV 416 to suggest investment strategies that may maximize FV 416. Each of these methodologies is described in more detail in application Ser. No. ______ entitled “Future Value Drivers,” to John J. Ballow et al., filed on Mar. 2, 2005 (Attorney reference 10022/625), the entire disclosure of which is hereby incorporated by reference.

Referring now to FIG. 4C, an exemplary visualization for displaying a TRS map 400 is shown. In the embodiment of FIG. 4C, a bar graph is used to visually convey the various components of a TRS map 400 to a user, and may be used to explain the TRS 402 for a particular period of time. For example, assume a company had a TRS 402 of $14,284 for a given period while paying $1000 in dividends 404 over that same period, resulting in a market value of equity 406 equal to $13,284. Further assuming a market value of debt 408 for the company of $9,184, the total market value of the company may be calculated at $22,467. Subtracting any excess cash 411 for the period leaves an enterprise value 412 of $21,731. If the company has an invested capital 420 of $12,276 and EP/WACC of ($2301), it can be calculated that the company's equity value 412 includes $9,974 of CV 414 and $11,757 of FV 416. Using the FV premium methodology 440, one can determine that the various components of FV 416 include a first portion 450 of $2,301 based on the expectation that the company will reach a breakeven economic profit, a second portion 452 of $8,010 based on an expected growth of the economy generally, and a third portion 454 of $1,446 which represents an expectation that the growth of the company will exceed that of the economy.

In FIGS. 5A-B an exemplary TRS statement detailing a Total Economic Profit (TEP) 510 calculation is shown. TEP represents one metric for annualizing and managing current and future value that bridges the gap between internal performance metrics and external metrics such as TRS. The TEP 510 of a company may be defined to include economic profit portions attributable to the current year, future value, capital charges, financing, and the like, or any combination thereof. The TEP 510 may be calculated for a given year, such as for tracking historical performance 520 of a company, or may be calculated for the enterprise as a whole. Additionally, change percentages 522 for the TEP may also be calculated. In one embodiment, the TEP 510 may also be used for target setting 530, described in more detail in application Ser. No. ______ entitled “TRS Target Setting,” to John J. Ballow et al., filed on Mar. 2, 2005 (Attorney reference 10022/627), the entire disclosure of which is hereby incorporated by reference. In the embodiment of FIGS. 5A-B, the TEP 510 is calculated by adding an EP 502 component, an invested capital charge 504, an EP of FV component 504, and an EP of financing component 504. The EP 502 component defines economic profit for the current value of the company for the given period, and may be calculated by multiplying the invested capital 540 of a company by its WACC 542 and subtracting the resultant value from company's NOPLAT 544. The invested capital charge 504 may be calculated by multiplying the company's invested capital 540 by the company's WACC 542. The Economic Profit of Future Value (EP of FV) 506 represents the economic profit of future value component 510 and may be calculated by multiplying the FV 546 of the company by its WACC 542. Optionally, the EP of finance 508 represents the portion of EP attributable to the company's financing arrangements. In one embodiment, the EP of finance 508 may be calculated by multiplying the dividends 548 paid for the period by the total number of outstanding shares 550 and dividing the resultant value by the company's WACC 542, such that the EP of finance 508=(Dividends per Share*Outstanding Shares)*WACC/WACC. Finally, the TEP 510 is calculated by adding the EP of CV 502, the capital charge 504, the EP of FV 506, and the EP of finance 510, so that the a capitalized change in TEP for a given period is equal to the TRS for that period.

The TEP can then be used to calculate the TRS for a given year. The TRS change for a given period can be calculated in dollars by calculating the change in TEP for the period (TEP at the end of the period minus TEP at the beginning of the period) and dividing the result by the WACC. Next, any change in debt is subtracted from the resultant value, and finally the dividends are added, such that the TEP ($)=(TEP2−TEP1)/WACC−Change in Debt+Dividends.

These calculations may also be represented as follows: $\begin{matrix} {{TRS\$} = {{MV2} - {MV1} + {Dividends}}} & \left( {{Eq}.\quad 1} \right) \\ {{{TRS}\%} = {{\left( {{MV2} - {MV1} + {Dividends}} \right)/{MV1}}*100}} & \left( {{Eq}.\quad 2} \right) \\ {{Where}\quad{MV2}\quad{is}\quad{the}\quad{market}\quad{value}\quad{of}\quad{equity}\quad{at}\quad{the}\quad{end}\quad{of}} & \quad \\ {{{the}\quad{period}},{{MV1}\quad{is}\quad{the}\quad{market}\quad{value}\quad{of}\quad{equity}\quad{at}\quad{the}}} & \quad \\ {{beginning}\quad{of}\quad{the}\quad{period}\quad{and}\quad{dividends}\quad{are}\quad{issued}\quad{during}} & \quad \\ {{the}\quad{{period}.}} & \quad \\ {{EP} = {{NOPLAT} - \left( {{Capital}*{WACC}} \right)}} & \left( {{Eq}.\quad 3} \right) \\ {\quad{= {{EP}\quad{of}\quad{CV}}}} & \quad \\ {{CV} = {{NOPLAT}/{WACC}}} & \left( {{Eq}.\quad 4} \right) \\ {\quad{= {{Capital} + {{EP}/{WACC}}}}} & \quad \\ {{MV} = {{Equity} + {Debt}}} & \left( {{Eq}.\quad 5} \right) \\ {\quad{= {{EV} + {{excess}\quad{cash}}}}} & \quad \\ {\quad{= {{cv} + {fv} + {{excess}\quad{cash}}}}} & \quad \\ {{EV} = {{equity} + {Debt} - {{excess}\quad{cash}}}} & \left( {{Eq}.\quad 6} \right) \\ {\quad{= {{mv} - {{excess}\quad{cash}}}}} & \quad \\ {{FV} = {{EV} - {CV}}} & \left( {{Eq}.\quad 7} \right) \\ {\quad{= {{Equity} + {Debt} - {{EP}/{WACC}} - {capital} - {{excess}\quad{cash}}}}} & \quad \\ {\quad{= {{Equity} + {Debt} - {{NOPLAT}/{WACC}} - {{excess}\quad{cash}}}}} & \quad \\ {{{EP}\quad{of}\quad{Fv}} = {{FV}*{WACC}}} & \left( {{Eq}.\quad 8} \right) \\ \text{(Decapitalizing~~Future~~Value)} & \quad \\ {{TEP} = {{{Capital}*{Wacc}} + {{EP}\quad{of}\quad{CV}} + {{EP}\quad{of}\quad{FV}} +}} & \left( {{Eq}.\quad 9} \right) \\ {\quad{{EP}\quad{of}\quad{Financing}}} & \quad \\ {{TRS} = {\left( {{{TEP2}/{WACC2}} - {{TEP1}/{WACC1}}} \right) - 1}} & \left( {{Eq}.\quad 10} \right) \end{matrix}$

Using annual TRS calculations allows a company to set target TRS values and decompose the TRS target (or shareholder expected returns) into values for Operating Capital and performance (CV), Growth (FV), and Financing. These additional values can then be further broken down, as described below. Indexing can be used to show performance in absolute and relative terms.

An exemplary TRS target worksheet using the TEP metric is shown in FIG. 6. Although the exemplary TRS worksheet of FIG. 6 contemplates TRS target setting, it should be apparent to one of ordinary skill in the art that a similar worksheet could be used to track historical performance of a company's TRS as well. Initially, a desired growth rate 602, dividend payment percentage 604, and debt/equity ratio 606 are established. In the example of FIG. 6, the company desires a ten percent growth rate 602, a five percent dividend payment 604, and a debt/equity ratio 606 of forty percent. Target TRS percentage changes 610 are then established for each of the desired year based on the growth percentage 602. Next, the TRS percentage changes 610 are converted to TRS dollar amount changes 612 for each year. The dividend targets 614 are calculated based on the desired dividend rate 604. Finally, the equity 616 and debt 618 values are calculated as a function of the desired debt/equity ratio 606. As the cost of equity (ke) is embedded in the WACC, setting a TRS target=ke assures meeting investor expectations ie. equity growth at ke.

From these values, the equations described above can be used to establish target values for additional performance metrics. These include targets for EV 620, EP of CV 622, FV 624, EP 626, EP of FV 628, and TEP 630. Finally, the annual TRS dollar change 632 can be calculated as a function of the TEP targets 630 to verify the calculations. These targets can then be decomposed further into targets for the drivers of each of these metrics to help the company reach these targets.

As noted above, the decomposition and mapping of the current and future value components of the total return to shareholders along with associated business processes or business components that drive those values provides valuable software tools for use in analyzing business performance and in managing the operation of those business components. As used herein, a business component may be an organizational sub-division of a company or enterprise. A business component also may be a business process within an enterprise that may be analyzed as an independent operation from a financial perspective.

In one embodiment, for example, a software tool may be provided on a laptop computer for use by a business consultant. In person-to-person interviews with a client, financial data may be input into a computer having a spreadsheet programmed to perform the calculations noted above. The spreadsheet may execute the calculations and presently generate reports on the display of the laptop for review by the consultant and client. The decomposition of shareholder value into component parts may displayed in graphical hierarchical maps that provide powerful depictions of hypothetical scenarios of the effect that drivers of business components have on current and future enterprise values.

In another embodiment, the program executing the calculations may be resident on computer-readable medium in a server in communication with a privately accessible data communication network, such as the internet or a WAN. The program may be accessed through a computer having a browser based interface to implement the same scenario identified above, or scenarios identified below.

Using the above spreadsheet or similarly programmed software tool implementing the method of this invention, one may quickly identify business component values that under perform industry benchmarks or corporate targets. The identified components may be candidates for further analysis to determine whether technology solutions may be provided to raise performance standards and enhance shareholder value. The spreadsheet or other software tool may include a library of standard technology solutions associated with each business component. Such solutions may be displayed or included in a report generated that describes the identified underperforming component and solutions that require further analysis for implementation to achieve benchmark or other target performance.

In yet another embodiment, the invention may be implemented in an enterprise as part of the business management software. A computer in communication with the financial accounting system may import financial data representative of the performance of a plurality of business components. The financial data may be manipulated to correspond with business components according to a map of business components identified as driving current or future value of shareholder returns. The financial data may then be analyzed in accordance with this invention to determine and display the expected actual shareholder return driven by the actual performance. Such data may be graphically displayed in a hierarchical map, or in the form of an executive dashboard. The actual performance financial data may be displayed along side with target values for various business component values. Colors, such as green, yellow, or red, for example, may be used to identify the relative performance, such as above, below, or greatly below target values assigned to individual business components. Additionally, acceptable tolerances for each business component target value may be established and reflected in the display. Such tools may be useful when integrated as monitoring tools into the business performance management frameworks, such as described in association with FIGS. 2 and 3.

In still another embodiment, the invention may be implemented in the form of a financial data provider. A database containing a historical store of financial data of corporation may be in communication on a publicly accessible network. For a fee, financial analysts may access such data and, using the software tools with on their own systems or on a server dedicated to this database, the financial analysts may map the components of shareholder value across broad swaths of industry segments. Also, the financial analysts may focus on a specific industry to determine industry benchmarks of component values. Those component benchmarks may be applied to generate financial report maps used for comparison purposes in making investment decisions with a specific company. Alternatively, the benchmarks may be used for comparison to identify which business components within a company are underperforming competitors, to enable business mangers to determine which business components require additional resources to maintain competitive performance levels.

In an alternative embodiment, the invention may be implemented in the form of target setting, forecasting, and budgeting tools in which targets are selected at a high level of management through a process of strategic planning to select targets based on a combination of value, such as TRS value for example, expected to be added and manageability of the candidate targets. In one embodiment, computer simulations of, inter alia, increased cash flows expected by the target strategies. These targets may then be flowed down to the various levels of management, budgets may be constructed around those target strategies, and the budgets may be consolidated and flowed upward. Alternatively, or additionally, the system may be used to increase shareholder value by improving forecasting abilities through the use of graphical representations of performance metrics of similarly situated companies in order to identify realistic value enhancing business strategies as goals for the organization. Exemplary systems of these types include those described in U.S. Patent Publication Nos. 2004/0073441 A1 and 2004/0073477 A1, both to Heyns et al., the entire disclosures of which are hereby incorporated by reference.

In still another embodiment, the invention may be implemented in a system for automatically examining a company's financial data and evaluating factors affecting the company's stock value. The system may, for example, evaluate a company's spread through that company's debt and equity costs and measure returns to investors from company growth, which may be either organic growth or growth through mergers and acquisitions. The system may also evaluate the financial data of other publicly traded companies, such as those in the same industry, and compares the various factors affecting stock value. The system may also include tools for determining the return to investors, such as a software-based application that collects receives financial data and uses this information to calculate the return to inventor through the company's spreads and growth. An exemplary systems of these types include those described in U.S. Patent Publication Nos. 2005/0004832 A1, to Ostergard et al., the entire disclosure of which is hereby incorporated by reference.

Another aspect of the invention provides comprehensive performance analysis of a company, and is illustrated in FIGS. 7-17. This embodiment includes a dynamic competitive modeling tool that allows one to interactively analyze a company's business strategy. The tool is suitable for analyzing the strategic environment of a company or business unit by graphically depicting the historical and forecasted performance of a company relative to its peers. Preferably the tool includes a financial model of a company's performance based on the TRS Mapping algorithms described above. By using the TRS Mapping algorithms, on the one hand, the tool can predict the market reaction to the operational and strategic plan to enable a company's management to wisely select a plan keeping shareholder expectations in mind. On the other hand, since the tool relies on publicly reported financial data, the tool can be used by outside analysts to benchmark a company's forecast performance for evaluating investment decisions.

The tool displays a company's historical performance metrics and embeds interactive inputs to permit a user to “dial-in” the forecasted financial metrics indicative of a company's operational and strategic planning. As a default, published forecasts may be used as the starting point for the analysis. These historical and forecasted metrics are dynamically tied into the powerful visualization tools to graphically depict the effect the inputted forecasted metrics have on multiple key performance measures, such as total return to shareholders. The tool has the capability to graphically depict the performance of selected peer companies on the same chart to provide a graphical comparison of the effect a selected operational and strategic plan may have relative to others.

As described in more detail below, the visualization tool has the capability to graphically depict financial performance on a single graph with four or five dimensions. The visualizations are effective to aid in competitive advantage analysis, such as the type described by Michael Porter in the classic text Competitive Analysis. Preferably, on one graph to evaluate profitability versus capital efficiency (FIG. 15), the five dimensions are profitability (Y-axis), capital utilization (X-axis), return on capital spread (iso-quants), market value (bubble size) and time (trend lines). Preferably, on a second graph to evaluate operating advantage versus strategic advantage (FIG. 16), the four dimensions are return on capital spread (Y-axis), Future Value efficiency (X-axis); market value (bubble size) and time (trend lines). The visualizations are interactive and dynamic in that the forecast metrics may be changed directly through input fields on the display and immediately the data is plotted on the graphs to graphically depict the change in the forecasted trends.

As shown in FIG. 7, the system 700 may include a plurality of data sources 710 a-710 n containing financial information, processing logic 720 for determining various performance metrics and information from the financial data, and a user interface 730 for collecting operator inputs 732 a-732 n and displaying various information, such as a summary report 734, intermediate reports 735, visualizations 736 a-736 n, and the like. Each of these components may be provided individually, or in combination with one another. The user interface 730 may also include navigation tools 738 for navigating among the various components of the interface 730, updating or refreshing the reports 734 and 735 or visualizations 736 a-736 n, and the like. For example, FIG. 17 shows an exemplary navigation tool 738 that includes a plurality of buttons 1702 each associated with a business unit being analyzed and a summary button 1704. Activation of the buttons 1702 and 1704 may cause the summary 734 and intermediate 735 reports to be updated with information related to the associated business unit or summary information, respectively.

Referring again to FIG. 7, the system may include a server 712 at a financial data provider with a large data store 714 of the reported financial data and prices of publicly traded financial instruments of publicly traded companies in one embodiment. Preferably, the data store contains historical data that may be provided or sold to others. The server 712 may be connected to a publicly accessible distributed data network, such as the Internet. Communications with the processing logic 720 may occur over such a network.

Processing logic 720, which may be maintained by a publicly traded company, is in communication with either the data sources 710 a-710 n, the server 712, or a combination of data sources 710 and servers 712. The processing logic 720 may be implemented as either software or hardware on a single computer or across multiple computers. The processing logic 720 may be in communication with a database 710 containing the companies' current and historical accounting and financial data. The processing logic 720 may also include modules for determining various performance metrics for a business unit associated with the company. The business units may include any component of the company for which financial data may be segregated, such as departments, subsidiaries, product lines, geographical regions, product SKUs and the like. In one embodiment, the business units may also include similar information for a competitor of the company, such as industry peers. Optionally or alternatively, the server 712 may be maintained by private investment analysts firms that analyze publicly traded companies and provide investment recommendations for private investors or the public. In such an embodiment, conventional periodic corporate financial reports may be obtained by the processing logic 720 from those servers 712.

The processing logic 720 may be configured to determine various performance metrics and information from the financial information. Such determinations may include calculations based on the received financial information as well as selecting metrics or information included in the received financial information. Alternatively, or in addition, the processing logic may be configured to project performance metrics and information from historical information (such as databases of historical information, annual reports, and the like), user inputs 732 a-732 n, or any combination therein. In one embodiment, the processing logic 720 may include logic for determining any or all of the following exemplary performance metrics and/or information: revenue growth, performance benchmarking, spread calculations, return on invested capital, NOPLAT and invested capital, NOPLAT (bottom up), NOPLAT (top down), cash taxes, invested capital (asset side), invested capital (liabilities side), investor fund, return on investment trees (with or without goodwill), operating working capital trees (with or without operating working capital. Table 1.0 includes exemplary financial data, performance metrics, and information which may be determined by the processing logic 720. TABLE 1.0 Company Name Country of Operations Currency Credit Rating Credit Ratings to be Used Int Exp on Operating Lease Int Exp on Retirement Liab Current Market Capitalization Operating Cash/Revenues Off-Balance Sheet Next Year's Operating Lease Expense Unfunded Pension Liability Unfunded Medical Benefits Income Statement Checks Amortization Check Operating Profit Check Interest Expense Check Interest Income Check Non-Operating Income Check Balance Sheet Checks Cash Check Goodwill Deferred Taxes Minority Interest Off-Balance Sheet Current Year's Operating Lease Expense Next Year's Operating Lease Expense Unfunded Pension Liability Unfunded Medical Benefits Years for Revenue Growth Revenue Revenue Growth (Year over Year) Avg Revenue Growth from Current Year Revenue Growth CAGR (Present Back to Year X + 1) Years for Performance Benchmarking COGS (w/o Depreciation & Amortization) COGS Margin Gross Income Gross Margin with D&A, not included in COGS) SG&A Margin EBITDA Margin Depreciation Margin Amortization Margin EBIT Margin Equity Market Cap Net Debt (Includes Operating Leases) Enterprise Value Years for Spread Calculations w/ or w/o Goodwill End of Year Spread w/o Goodwill End of Year Spread w/Goodwill Average Spread w/o Goodwill Average Spread w/Goodwill Years for Spread Calculations w/ or w//o NGW Average Spread w/o NGW Average Spread w/NGW Years for Return on Invested Capital End of Year ROIC without Net Goodwill End of Year ROIC with Net Goodwill Mid-Year ROIC w/o NGW Average ROIC w/Goodwill NOPLAT Reconciliation Invested Capital Reconciliation Revenues COGS (w/o Dep & Amort) Operating Lease Expense Retirement Related Liabilities (RLL) Expense SG&A Other Operating Expenses Depreciation & Amortization Expense Adjusted EBIT Amortization Expense EBITA Cash Taxes on EBITA NOPLAT (Cash Tax Rate) NOPLAT (Bottoms up) Reported Net Income Deferred Taxes Amortization Extraordinary Items Minority Interest Adjusted Net Income After Tax Interest Expense Interest Income after taxes After Tax Non-Operating Income After Tax Op Leases After Tax Retirement Related Liabilities (RLL) NOPLAT Marginal Tax Rate (based on country of Operations) Interest Income Interest Expense Operating Leases Retirement Expenses Non-Operating Expense, Net Provision for Income Taxes Change in Deferred Taxes Tax on Interest Income Tax Shield on Interest Expense Tax on Operating Leases Tax Shield on Retirement-related Liabilities Tax on non-operating Income Cash Taxes on EBITA Operating Cash Accounts Receivables Inventory Other Current Assets Operating Current Assets Accounts Payable Income Taxes Payable Other Current Liabilities Non-Interest bearing Current Liabilities Operating Working Capital Net PPE Implied Value of Operating Leases Other Operating Assets Other Operating Liabilities Implied Value of Unfunded Retirement Liabilities Invested Capital (w/o Goodwill) Net Goodwill Invested Capital w/Goodwill Excess Cash and Securities Non-Operating Investments Total Investor Funds Invested Capital (Liabilities Side/Where From) Shareholders Equity Minority Interest Adjusted Equity All Interest Bearing Debt (including Operating Leases and Return Liabilities) Deferred Income Taxes Cumulative Goodwill Amortization Total Investor Fund Average ROIC PreTax ROIC Cash Tax Rate on EBITA EBITA/Revenues COGS/Revenues SG&A/Revenues Other Operating Expenses/Revenues Depreciation/Revenues Revenues/Invested Capital Operating Working Capital/Revs Net PPE/Revs Net Other assets/Revs Goodwill/Revs Revenues Year over Year Growth ROIC (w/o goodwill) PreTax ROIC Cash Tax Rate on EBITA EBITA/Revenues COGS/Revenues SG&A/Revenues Other Operating Expenses/Revenues Depreciation/Revenues Revenues/Invested Capital Operating Working Capital/Revs Net PPE/Revs Other assets/Revs Operating Working Capital Operating Curr. Assets/Rev Non Interest Bearing Current Liabilities/Revenue Cash/Rev Net Receivables/Rev Inventory/Rev Other Current Assets/Rev Accounts Payable/Rev Income Taxes Payable/Rev Other Current Liabilities Risk Free Rate Market Risk Premium Beta Market Capitalization Total Debt Total Value Ke Credit Rating Kd Tax Rate WACC End of Year Spread w/o Goodwill End of Year Spread w/Goodwill Average Spread w/o Goodwill Average Spread w/Goodwill Average Spread w/o NGW Average Spread w/NGW End of Year ROIC without Net Goodwill End of Year ROIC with Net Goodwill Mid-Year ROIC w/o NGW Average ROIC w/Goodwill Invested Capital Reconciliation Revenues COGS (w/o Dep & Amort) Operating Lease Expense Retirement Related Liabilities (RLL) Expense SG&A Other Operating Expenses Depreciation & Amortization Expense Adjusted EBIT Amortization Expense EBITA Marginal Taxes on EBITA NOPLAT (Marg. Tax Rate) Operating Cash Accounts Receivables Inventory Other Current Assets Operating Current Assets Accounts Payable Income Taxes Payable Other Current Liabilities Non-Interest bearing Current Liabilities Operating Working Capital Net PPE Implied Value of Operating Leases Other Operating Assets Other Operating Liabilities Implied Value of Unfunded Retirement Liabilities Net Goodwill Invested Capital w/Goodwill Excess Cash and Securities Non-Operating Investments Total Investor Funds Shareholders Equity Minority Interest Adjusted Equity All Interest Bearing Debt (including Operating Leases and Return Liabilities) Deferred Income Taxes Cumulative Goodwill Amortization Total Investor Fund Average ROIC PreTax ROIC Marginal Tax Rate on EBITA EBITA/Revenues COGS/Revenues SG&A/Revenues Other Operating Expenses/Revenues Depreciation/Revenues Revenues/Invested Capital Operating Working Capital/Revs Net PPE/Revs Net Other assets/Revs Goodwill/Revs Revenues Year over Year Growth ROIC (w/o goodwill) PreTax ROIC Marginal Tax Rate on EBITA EBITA/Revenues COGS/Revenues SG&A/Revenues Other Operating Expenses/Revenues Depreciation/Revenues Revenues/Invested Capital Operating Working Capital/Revs Net PPE/Revs Other assets/Revs Operating Working Capital Operating Curr. Assets/Rev Non Interest Bearing Current Liabs/Rev Cash/Rev Net Receivables/Rev Inventory/Rev Other Current Assets/Rev Accounts Payable/Rev Income Taxes Payable/Rev Other Current Liabilities Risk Free Rate Market Risk Premium Beta Market Capitalization Total Debt Total Value Ke Credit Rating Kd Tax Rate WACC Normalized NOPLAT Enterprise Value Value of Current Operations Weight Value of Future Operations Weight Normalized NOPLAT Enterprise Value w/o Excess Cash Value of Current Operations CV Weight w/o Excess Cash Value of Future Operations w/o Excess Cash FV Weight w/o Excess Cash Interest Coverage Ratio Debt/Equity Ratio EVA Market Value Added NOPLAT Less: Capital Charge Economic Profit Revenue per Employee Market/Book Ratio Book Value Benchmarking Averages 5 Year TRS (CAGR) 4 Year TRS (CAGR) 3 Year TRS (CAGR) 5 Year Average Spread (w/NGW) 4 Year Average Spread (w/NGW) 3 Year Average Spread (w/NGW) 5 Year Average Spread (without NGW) 4 Year Average Spread (without NGW) 3 Year Average Spread (without NGW) 5 Year Average Revenue Growth 4 Year Average Revenue Growth 3 Year Average Revenue Growth 5 Year Average ROIC (with Goodwill) 4 Year Average ROIC (with Goodwill) 3 Year Average ROIC (with Goodwill) 5 Year Average ROIC (without Goodwill) 4 Year Average ROIC (without Goodwill) 3 Year Average ROIC (without Goodwill) 5 Year Average EBITA/Revenue 4 Year Average EBITA/Revenue 3 Year Average EBITA/Revenue 5 Year Average Revenue/Invested Capital (w/Goodwill) 4 Year Average Revenue/Invested Capital (w/Goodwill) 3 Year Average Revenue/Invested Capital (w/Goodwill) 5 Year Average Debt/Equity Ratio 4 Year Average Debt/Equity Ratio 3 Year Average Debt/Equity Ratio 5 Year Average Revenue/Employee 4 Year Average Revenue/Employee 3 Year Average Revenue/Employee Gross Property, Plant and Equipment-STANDARD SVA RATIOS Depreciation, Depletion and Amortization (Accumulated), Plant and Equipment Net Property, Plant and Equipment Amortization (Accumulated) Dec. (Inc.) in Invested Capital w/o Goodwill Free Cash Flow Capital Expenditures Depreciation and Amortization Expense Reinvestment Multiple Gross Property, Plant and Equipment Depreciation and Amortization Expense Estimated Useful Life of Gross PP&E Accumulated Depreciation and Amortization Depreciation and Amortization Expense Estimated Age of Depreciable Assets Employee Sales/Employee Operating Assets/Employee Operating Asset Turnover Net Annual Sales Average Receivables A/R Turnover Average A/R Collection Period = 365/A/R Turnover Cost of Goods Sold Average Inventory Inventory Turnover Average Inventory Processing Period = 365/Inventory Turnover Cost of Goods Sold Average Trade Payables A/P Turnover Ratio A/P Payment Period = 365/A/P Turnover Ratio Average A/R Collection Period Average Inventory Processing Period Payables Payment Period Cash Conversion Cycle NOPLAT WACC Future Value Economic Profit EP/WACC Future Value MVA MVA Check Shares Outstanding (Total at Year-End)

The processing logic 720 may also be in communication with the user interface 730. In one embodiment, the processing logic 720 may receive inputs 732 a-732 n from the user interface 730, determine various performance metrics and information for a business unit of a company based any combination of the inputs 732 a-732 n and the financial data received from the various data sources 710 a-710 n, and generate summary information 736 and/or visualizations 736 a-736 n which may display data points related to the performance metrics or information.

Referring now to FIGS. 8-13, exemplary intermediate reports 735 are shown. These intermediate reports 735 may be provided with or without inputs 732 a-732 n. The purpose of these intermediate reports 735 are to provide additional performance metrics and information to the visualizations 736 a-736 n and summary report 734 to enrich the analysis provided by the system 700, as well as to provide a logical vehicle for receiving inputs 732 a-732 n related to the performance metrics and information included in the intermediate reports 732. Therefore, the intermediate reports 735 preferably include a combination of historical data and projected data.

The exemplary summary forecast report 735 [800] of FIG. 8 includes historical data and forecasted data for the revenue growth 802, operating profit margin (NOPLAT/Revenue) 804, Operating Lease Growth 806, Capital Expenditures 808. The forecasted data may be as a default based on published forecast estimates, or may accept data input in the respectrive fields732 a, 732 b, 732 c, 732 d, and 732 e. The data may be input simply by the use of active arrows to be clicked to increase or decrease the forecast changes of the metrics 802-810. The historical data associated with these metrics may include at least data for the current period and optionally data for prior periods. Preferably, the metrics shown in FIG. 8 are key variables that are used to calculate data on the multi-dimensional axes of the forecast analytical visualizations depicted in FIGS. 15 and 16. Accordingly, it is preferred that the summary report of FIG. 8 be displayed together with the visualizations of FIGS. 15 and 16 so that a user may change a forecasted metric and see the graphically represented change on future prospects of the business unit.

Referring to FIG. 9, another exemplary intermediate report 735 [900] is shown. The report 735 [900] may include metrics and information for calculating a top down NOPLAT. Exemplary top down NOPLAT metrics and information may include Cost of Goods Sold (COGS) 902 and marginal tax rate 904 historical data and future projection inputs 732 f and 732 g, respectively. Additional exemplary metrics and information 906 for a top down NOPLAT calculation may include gross margin, next year's operating lease expense, cost of debt, implied value of operating leases, operating lease expense, retirement related liabilities (RLL) expense, SBU SG&A, corporate SG&A, other operating expenses, depreciation and amortization expense, adjusted EBIT, amortization expense, marginal taxes on EBITA, operating profit (NOPLAT growth), and operating profit margin (NOPLAT/revenue).

Referring to FIG. 10, yet another exemplary intermediate report 735 without inputs 732 is shown. In the embodiment of FIG. 10, the report 735 [1000] may include metrics and information for invested capital related calculations. Such information may be provided for both historic and projected financial information. Exemplary invested capital related metrics and information 1002 may include operating cash, accounts receivable, inventory, other current assets, operating current assets, accounts payable, income taxes payable, other current liabilities, non-interest bearing current liabilities, operating working capital, net PPE, implied value of operating leases, other operating assets, other operating liabilities, implied value of unfunded retirement liabilities, net goodwill, invested capital (with goodwill), gross property, plan and equipment, accumulated depreciation, net property, plant, and equipment, depreciation and amortization, and capital expenditures.

Referring to FIG. 11, still another exemplary intermediate report 735 [1100] including metrics and information related to multiple calculations is shown. In the embodiment of FIG. 11, the report 735 [1100] may include historic and projected metrics and information for free cash flow, common stock repurchase, dividends payable, and free cash flow valuation calculations. Exemplary free cash flow related metrics and information 1106 may include NOPLAT, incremental decline in invested capital, and free cash flow. Exemplary common stock repurchase related metrics and information 1108 may include outstanding common shares beginning balance, common shares to repurchase 1102 and associate input 732 h, and outstanding common shares ending balance. Exemplary dividends payable related metrics and information 1110 may include dividend payable per quarter share 1104 and associated input 732 i, annual dividend payout per share, total dividend payout, and payout ratio as a percentage of free cash flow available. Exemplary free cash flow valuation related metrics and information 1112 may include terminal value, discount rate, discounted cash flow, discounted terminal value, expected firm value, market value of book debt, equity, and expected share price.

Referring to FIG. 12, another exemplary intermediate report 735 [1200] including metrics and information related to multiple calculations without inputs is shown. In the embodiment of FIG. 12, the report 735 [1200] may include TRS targets and FV/CV analysis metrics and information for both historic and projected data. Exemplary TRS target related metrics and information 1202 may include WACC, cost of debt, cost of equity, current market value, projected market value, market value of book debt, ST and LT debt and operating leases, dividends, total TRS in dollars, growth in TRS in dollars, equity share price target, and TRS targets. Exemplary FV/CV analysis related metrics and information 1204 may include market capitalization, projected debt, projected enterprise value, projected current value, projected future value, current value percentage of enterprise value, and future value percentage of enterprise value.

Referring to FIG. 13, another exemplary intermediate report 735 [1300] including metrics and information without inputs is shown. In the embodiment of FIG. 13, the report 735 [1300] may include ratio analysis metrics and information for both historic and projected data. Exemplary ratio analysis metrics and information 1302 may include historical earning, earnings/NOPLAT multiple, revenue/invested capital, capital charge, revenue/capital charge, future value/invested capital, revenue growth, capital growth, spread, economic profit (spread*invested capital), economic profit (NOPLAT−(invested capital*WACC), economic profit check, sustainable growth, future value check, dividends per share, and TRS.

As described above, the processing logic 720 may also generate one or more summary reports 734. Referring to FIG. 14, an exemplary summary report 734 [1400] is shown. In one embodiment, the summary report may include metrics and information for a particular business unit. Alternatively, or in addition, a summary report 734 [1400] may be configured to include performance metrics and information for every business unit being analyzed, such as averages or totals for all business units. Preferably, the summary report 734 [1400] includes both historic and projected metrics and information. Exemplary metrics and information 1402 may include revenue, operating profit (NOPLAT), invested capital with goodwill, return on invested capital, capital turns, projected current value, projected future value, expected share price (free cash flow valuation), price/earnings ratio (P/E), earnings per share (EPS), and TRS.

Additionally, the processing logic 720 may generate one or more visualizations 736 a-736 n for displaying metrics and information. The system 700 may be configured to show a single visualization at a time, or multiple visualizations may be shown simultaneously. In alternate embodiments, a slide show of visualizations may be presented to a user showing the implementation of alternative strategies or different aspects of the same strategy.

Referring to FIG. 15, an exemplary visualization 736 a [1500] is shown. In the embodiment of FIG. 15, the processing logic 720 may determine a plurality of data points based on financial data received from various data source 710 a-710 n. Each data may be associated with a particular business unit, and each business unit may be associated with more than one depicted data point. For example, each business unit may have a corresponding data point depicted for a each time period. For example, data points may be calculated for each business unit for year-end, semi-annually, quarterly, monthly, weekly, or daily time period.

In one embodiment, the visualization may graphically depict the performance of a business unit over five dimensions or data components. Preferably, each data point includes a first component based on the NOPLAT/revenue 1502 metric value for the associated business unit. Additionally, each data point may include a second component based on the revenue/capital charge 1504 metric value for the associated business unit. By plotting a graph using these two components, the visualization 736 a [1500] may provide a chart of profitability versus capital efficiency for the associated business unit. These components also enable the visualization 736 a [1500] to include indicia 1506 that indicate a spread percentage for the business unit. In one embodiment, the indicia 1506 may include isoquants associated with particular spread percentage values. Optionally, each data point may also include indicia 1508 indicative of the invested capital of the business unit, such as a size, color, or the like associated with the data point.

The visualization 736 a [1500] may also include multiple data points for each business unit. For example, data points may be determined for each of a plurality of time periods. In the embodiment of FIG. 15, data point 1510 corresponds to a data point determined at a first time and data point 1512 corresponds to a data point determined at a second time. In such an embodiment, an indicia 1514 indicative of the relationship between the data points of a particular business unit, such as a line or curve connecting the data points, may also be included. Plotting data points for each of a plurality of business units across time and in the manner described above allows an individual to quickly and easily determine trends, strategies, and efficiencies for a particular group of related business units.

Referring now to FIG. 16, another exemplary visualization 736 b [1600] is shown. This visualization 736 b [1600] is similar to the visualization 736 a [1500] of FIG. 15 in many respects, however, is designed to provide operating advantage versus strategic advantage information. First, the visualization 736 b [1600] includes a plurality of data points corresponding to performance metrics and information associated with various business units. Each data point includes at least a first and second component. In the embodiment of FIG.16, the first component is based on the spread percentage 1602 of the business unit, while the second component is based on the ratio of future value over the invested capital plus goodwill of the business unit. Additionally, each data point includes indicia 1608 indicative of the invested capital for the business unit. In one embodiment, multiple data points may be included for each business unit. For example, the visualization 736 b [1600] may include a first data point 1610 determined for a first time for the business unit and a second data point 1612 determined for a second time for the business unit. Indicia 1614 may also be included for showing a relationship between the data points 1610 and 1612.

Based on the teachings described herein, others of ordinary skill in the art will appreciate other applications of the system, apparatus and methods in accordance with this invention. Accordingly, it is therefore intended that the foregoing detailed description be regarded as illustrative rather than limiting, and that it be understood that it is the following claims, including all equivalents, that are intended to define the spirit and scope of this invention. 

1. A computer-implemented method for analyzing the relative performance of a business unit of a company, the method comprising: receiving financial data about the business unit; determining with a data processor NOPLAT, revenue, capital charge, and invested capital values for the business unit at least at a first time and a second time from the financial data; determining with the data processor at least two data point from the NOPLAT, revenue, capital charge, and invested capital values, each data point including a first component indicative of NOPLAT/revenue for the business unit and a second component indicative of revenue/capital charge for the business unit, the at least two data points indicative of values determined at one of the first time and the second time, respectively; and displaying the at least two data points, a first indicia for each data point indicative of the capital value, a second indicia indicative of a spread percentage, and a third indicia indicative of a relationship between the at least two data points between the first time and the second time, so as to advise a user of the performance of the business unit,
 2. The computer-implemented method of claim 1, wherein the business unit includes a business unit type selected from group consisting of the company, a product line, a geographical region, an SKU, a competitor of the company, a competitor's product line, a competitor's geographical region, or a competitor's SKU.
 3. The computer-implemented method of claim 1, wherein the first indicia comprises a size for the associated data point.
 4. The computer-implemented method of claim 1, wherein the displaying further comprises displaying a graph, wherein the second indicia comprises at least one isoquant indicative of a spread percentage for the business unit on the graph.
 5. The computer-implemented method of claim 1, wherein the received financial data further comprises financial data about a second business unit different from the business unit, the computer-implemented method further comprising: determining with the data processor NOPLAT, revenue, capital charge, and invested capital values for the second business unit at least at the first time and the second time from the financial data; determining with the data processor at least two second data points from the NOPLAT, revenue, capital charge, and invested capital values, each second data point including a first component indicative of NOPLAT/revenue for the second business unit and a second component indicative of revenue/capital charge for the second business unit, the at least two second data points indicative of values determined at one of the first time and the second time, respectively; and displaying, to advise a user of the performance of the business unit and the second business unit, the at least two second data points, a fourth indicia for each second data point indicative of the capital value, and a fifth indicia indicative of a relationship between the at least two second data points between the first time and the second time.
 6. The computer-implemented method of claim 5, wherein the second business unit includes a business unit type selected from group consisting of the company, a product line, a geographical region, an SKU, a competitor of the company, a competitor's product line, a competitor's geographical region, or a competitor's SKU.
 7. The computer-implemented method of claim 6, wherein the business unit and the second business unit are of the same business unit type.
 8. The computer-implemented method of claim 1 further comprising: projecting with the data processor NOPLAT, revenue, capital charge, and invested capital values for the business unit for a third time in the future; projecting with the data processor a third data point from the NOPLAT, revenue, capital charge, and invested capital values, each third data point including a first component indicative of NOPLAT/revenue for the business unit and a second component indicative of revenue/capital charge for the business unit, the third data point indicative of values projected for the third time; and displaying, to advise a user of the performance of the business unit, the third data point.
 9. The computer-implemented method of claim 8, further comprising: receiving an operator input indicative of a growth percentage for at least one of the group consisting of the NOPLAT, revenue, capital charge, and invested capital values for the business unit; and projecting with the data processor at least one of NOPLAT, revenue, capital charge, and invested capital values for the business unit for the third time in the future in accordance with the operator input.
 10. The computer-implemented method of claim 5 further comprising: projecting with a data processor NOPLAT, revenue, capital charge, and invested capital values for the business unit and the second business unit for a third time in the future; projecting with a data processor a third data point and a fourth data point from the NOPLAT, revenue, capital charge, and invested capital values, each third data point and fourth data point including a first component indicative of NOPLAT/revenue for the business unit the second business unit, respectively, and a second component indicative of revenue/capital charge for the business unit and the second business unit, respectively, the third data point and the fourth data point indicative of values projected for the third time; and displaying, to advise a user of the performance of the business unit and the second business unit, the third data point and the fourth data point, wherein the third indicia is further indicative of a relationship between the at least one of the at least two data points and the third data point and the fifth indicia is further indicative of a relationship between at least one of the at least two second data points and the fourth data point.
 11. The computer-implemented method of claim 10, further comprising: receiving an operator input indicative of a growth percentage for at least one of the group consisting of the NOPLAT, revenue, capital charge, and invested capital values for the second business unit; and projecting with the data processor at least one of NOPLAT, revenue, capital charge, and invested capital values for the second business unit for the third time in the future in accordance with the operator input.
 12. A computer-implemented method for analyzing the relative performance of a business unit of a company, the method comprising: receiving financial data about the business unit; determining with a data processor spread percentage, future value, and invested capital values for the business unit at least at a first time and a second time from the financial data; determining with a data processor at least two data point from the spread percentage, future value, and invested capital values, each data point including a first component indicative of spread percentage for the business unit and a second component indicative of future value/invested capital for the business unit, the at least two data points indicative of values determined at one of the first time and the second time, respectively; and displaying, to advise a user of the performance of the business unit, the at least two data points, a first indicia for each data point indicative of the invested capital value and a second indicia indicative of a relationship between the at least two data points between the first time and the second time.
 13. The computer-implemented method of claim 12, wherein the business unit includes a business unit type selected from group consisting of the company, a product line, a geographical region, an SKU, a competitor of the company, a competitor's product line, a competitor's geographical region, or a competitor's SKU.
 14. The computer-implemented method of claim 12, wherein the first indicia comprises a size for the associated data point.
 15. The computer-implemented method of claim 12, wherein the received financial data further comprises financial data about a second business unit different from the business unit, the computer-implemented method further comprising: determining with spread percentage, future value, and invested capital values for the second business unit at least at the first time and the second time from the financial data; determining with a data processor at least two second data points from the spread percentage, future value, and invested capital values, each second data point including a first component indicative of spread percentage for the business unit and a second component indicative of future value/invested capital for the business unit, the at least two second data points indicative of values determined at one of the first time and the second time, respectively; and displaying, to advise a user of the performance of the business unit and the second business unit, the at least two second data points, a third indicia for each second data point indicative of the invested capital value, and a fourth indicia indicative of a relationship between the at least two second data points between the first time and the second time.
 16. The computer-implemented method of claim 15, wherein the second business unit includes a business unit type selected from the group consisting of the company, a product line, a geographical region, an SKU, a competitor of the company, a competitor's product line, a competitor's geographical region, or a competitor's SKU.
 17. The computer-implemented method of claim 16, wherein the business unit and the second business unit are of the same business unit type.
 18. The computer-implemented method of claim 15 further comprising: projecting with a data processor spread percentage, future value, and invested capital values for the business unit for a third time in the future; projecting with a data processor a third data point from the spread percentage, future value, and invested capital values, each third data point including a first component indicative of spread percentage for the business unit and a second component indicative of future value/invested capital for the business unit, the third data point indicative of values projected for the third time; and displaying, to advise a user of the performance of the business unit, the third data point.
 19. The computer-implemented method of claim 18, further comprising: receiving an operator input indicative of a growth percentage for at least one of the group consisting of the spread percentage, future value, and invested capital values for the business unit; and projecting with the data processor at least one of spread percentage, future value, and invested capital values for the business unit for the third time in the future in accordance with the operator input.
 20. The computer-implemented method of claim 15 further comprising: projecting with a data processor spread percentage, future value, and invested capital values for the business unit and the second business unit for a third time in the future; projecting with a data processor a third data point and a fourth data point from the spread percentage, future value, and invested capital values, each third data point and fourth data point including a first component indicative of spread percentage for the business unit and the second business unit, respectively, and a second component indicative of future value/invested capital for the business unit and the second business unit, respectively, the third data point and the fourth data point indicative of values projected for the third time; and displaying, to advise a user of the performance of the business unit and the second business unit, the third data point and the fourth data point, wherein the third indicia is further indicative of a relationship between the at least one of the at least two data points and the third data point and the fifth indicia is further indicative of a relationship between at least one of the at least two second data points and the fourth data point.
 21. The computer-implemented method of claim 20, further comprising: receiving an operator input indicative of a growth percentage for at least one of the group consisting of the spread percentage, future value, and invested capital values for the second business unit; and projecting with the data processor at least one of the spread percentage, future value, and invested capital values for the second business unit for the third time in the future in accordance with the operator input.
 22. A computer-implemented method for analyzing the relative performance of a business unit of a company, the method comprising: receiving publicly available historical financial data forecast financial data in an electronic readable format about a plurality of business units from a data source; calculating with a data processor a plurality of ratios of financial performance measures based on the received financial data; selecting a business unit from the plurality of business units and populating a plurality of report templates with the received data and calculated ratios for the selected business unit; displaying the plurality of report templates; receiving inputs of forecasted change in performance measures or calculated ratios through active input fields on the displayed templates; pre-defining a plurality of the ratios to represent the major axes of one or more displayed graphs; selecting a first ratio for a first axis of a displayed graph and selecting a second ratio for a second axis of the displayed graph, wherein the first ratio and the second ratio are calculated from a common metric such that the first and second ratio have a relationship that results in a series of isoquants being defined and depicted on the graph; depicting on the graph for each business unit a line connecting a plurality of data points corresponding to the calculated first and second ratios for a plurality of predefined time periods; wherein each data point is depicted by a circle, the diameter of which corresponds to a financial metric associated with the business unit at the corresponding time period.
 23. The computer-implemented method of claim 22, further comprising displaying a navigation tool on the same screen display with the graph having active buttons, which when activated by a user selects the business unit from the plurality of business units for which the data is populated on the templates.
 24. The computer-implemented method of claim 23, wherein the data processor updates the calculated ratios and performance metrics upon receiving a changed value in an input field and substantially immediately thereafter graphs the new data points reflective of the updated ratios and performance metrics.
 25. The computer-implemented method of claim 20, further comprising selecting a series of displayed colors to fill in the circles; wherein each color represents a selected time period. 